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de Weck, A.

Publications and source records attributed to de Weck, A..

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Analysis of head and neck carcinoma progression reveals novel and relevant stage-specific genetic changes associated with immortalisation and malignancy.

Head and neck squamous cell carcinoma (HNSCC) is a widely prevalent cancer globally with high mortality and morbidity. We report here changes in the genomic landscape in the development of HNSCC from potentially premalignant lesions (PPOLS) to malignancy and lymph node metastases. Frequent likely pathological mutations are restricted to a relatively small set of genes including TP53, CDKN2A, FBXW7, FAT1, NOTCH1 and KMT2D; these arise early in tumour progression and are present in PPOLs with NOTCH1 mutations restricted to cell lines from lesions that subsequently progressed to HNSCC. The most frequent genetic changes are of consistent somatic copy number alterations (SCNA). The earliest SCNAs involved deletions of CSMD1 (8p23.2), FHIT (3p14.2) and CDKN2A (9p21.3) together with gains of chromosome 20. CSMD1 deletions or promoter hypermethylation were present in all of the immortal PPOLs and occurred at high frequency in the immortal HNSCC cell lines (promoter hypermethylation ~63%, hemizygous deletions ~75%, homozygous deletions ~18%). Forced expression of CSMD1 in the HNSCC cell line H103 showed significant suppression of proliferation (p=0.0053) and invasion in vitro (p=5.98X10-5) supporting a role for CSMD1 inactivation in early head and neck carcinogenesis. In addition, knockdown of CSMD1 in the CSMD1-expressing BICR16 cell line showed significant stimulation of invasion in vitro (p=1.82 x 10-5) but not cell proliferation (p=0.239). HNSCC with and without nodal metastases showed some clear differences including high copy number gains of CCND1, hsa-miR-548k and TP63 in the metastases group. GISTIC peak SCNA regions showed significant enrichment (adj P<0.01) of genes in multiple KEGG cancer pathways at all stages with disruption of an increasing number of these involved in the progression to lymph node metastases. Sixty-seven genes from regions with statistically significant differences in SCNA/LOH frequency between immortal PPOL and HNSCC cell lines showed correlation with expression including 5 known cancer drivers.\n\nLay SummaryCancers affecting the head and neck region are relatively common. A large percentage of these are of one particular type; these are generally detected late and are associated with poor prognosis. Early detection and treatment dramatically improve survival and reduces the damage associated with the cancer and its treatment. Cancers arise and progress because of changes in the genetic material of the cells. This study focused on identifying such changes in these cancers particularly in the early stages of development, which are not fully known. Identification of these changes is important in developing new treatments as well as markers of behaviour of cancers and also the early or premalignant lesions. We used a well-characterised panel of cell lines generated from premalignant lesions as well as cancers, to identify mutations in genes, and an increase or decrease in number of copies of genes. We mapped new and previously identified changes in these cancers to specific stages in the development of these cancers and their spread. We additionally report here for the first time, alterations in CSMD1 gene in early premalignant lesions; we further show that this is likely to result in increased ability of the cells to spread and possibly, multiply faster as well.

cancer biology

Fibroblasts cell lines misclassified as cancer cell lines

Large collections of immortalized cancer cell lines have been widely used as model systems for cancer research and drug discovery. Some of these models however display more fibroblast-like than cancer-like characteristics based on their genetic and genomic characterization. The correct annotation of these cell lines remains a challenge. Here, we report the outcome of our analysis on a large cancer cell line collection, where we found a subset of cell lines misclassified.

cancer biology

Correction of copy number induced false positives in CRISPR screens

Cell autonomous cancer dependencies are now routinely identified using CRISPR loss-of-function screens. However, a bias exists that makes it difficult to assess the true essentiality of genes located in amplicons, since the entire amplified region can exhibit lethal scores. These false-positive hits can either be discarded from further analysis, which in cancer models can represent a significant number of hits, or methods can be developed to rescue the true-positives within amplified regions. We propose two methods to rescue true positive hits in amplified regions by correcting for this copy number artefact. The Local Drop Out (LDO) method uses the relative lethality scores within genomic regions to assess true essentiality and does not require additional orthogonal data (e.g. copy number value). LDO is meant to be used in screens covering a dense region of the genome (e.g. a whole chromosome or the whole genome). The General Additive Model (GAM) method models the screening data as a function of the known copy number values and removes the systematic effect from the measured lethality. GAM does not require the same density as LDO, but does require prior knowledge of the copy number values. Both methods have been developed with single sample experiments in mind so that the correction can be applied even in smaller screens. Here we demonstrate the efficacy of both methods at removing the copy number effect and rescuing hits from some of the amplified regions. We estimate a 70-80% decrease of false positive hits in regions of high copy number with either method.

bioinformatics